• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.333-337
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• 2006

The purpose of this paper is to present a strategic approach to selecting prior areas of soil erosion to be examined for effective soil conservation planning and management, in conjunction with remote sensing data and GIS skill for surface characteristics. To do this, two basins are selected: Andong and Imha basin. Geographically one is in the vicinity of the other but turbidity in the main reservoir of each basin is quite different. it is important to clarify general behavior of soil erosion driven by rainfall event for both basins for further understanding and effective soil conservation planning and management. Also, Both basins are divided into several sub-basins and the severity of soil loss is intensively investigated to identify areas with high erosion potential for each sub-basin so that the efficiency of soil conservation program may increase. Especially, this study analyzed soil erodibility factor(K), topographic factor(LS), cover management factor(C) and soil erosion; 3 sub-basins for Andong basin (up-, mid-, downstream) and 6 sub-basins for Imha basin (up-, mid-, and downstream for two tributaries) because Imha basin consists of two tributaries (Banyeon and Yongjeon river). The approach suggested herein will provide a guideline for choosing prior areas to be examined and managed for soil conservation planning.

• Spatial Information Research
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• v.2 no.2
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• pp.165-174
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• 1994

Soil loss was estimated by using universal soil loss equation(USLE) through GIS technique in Buyeu area. The expected soil loss is determined from six environmental factors: rainfall, erodibility of selected soil, length and steepness (gradient) of ground slope, crop grown in soil, and land practices used. A scoring system for assessing soil lossrisk has been developed for calculating SLI(Soil Loss Index) by GIS. The scores of six factors multiplied to give a total score which was compared with an chosen classification system to categorize areas of low, moderate and high risk. Finally, a soil loss assessment map was produced by GIS cartographic simulation technique, and this map could be applied in the establishment of regional land use planning.

• Korean Journal of Soil Science and Fertilizer
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• v.11 no.3
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• pp.145-160
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• 1979

The effects of organic material application on soil physical properties were reviewed in relation to soil productivity. The organic matter contents and soil physical properties of the cultivated land in Korea were summarized and the effects of organic matter were compared in terms of land uses and soil types. Soil physical properties related to crop yield potential, such as soil aggregation, permeability, water holding capacity, erodibility, and compactibility, were used in evaluating the effects of organic materials as a soil physical amendment. The benefical effects of organic matter addition on soil physical conditions include (1) better aeration and increased infiltration in silty and clayey soils, (2) increased water holding capacity and moisture availability in sandy soils, (3) decreased soil erodibility, and (4) increased resistance to compaction. It is, therefore, concluded that continuous application of organic materials could greatly improve the various soil physical properties and favor the growth and yield of crops. A high rate of organic matter addition could contribute to reducing not only the soil erosion on sloping land, but also the possible detrimental effect of farm mechanization. In general, the effects of organic matter on soil physical improvement were estimated to be much higher in upland than in paddy. Organic matter would have a more pronounced effect on low productive lands such as heavy clayey or sandy soils and newly reclaimed soil. The optimum level of soil organic matter content was estimated to be about 3.0 to 3.5% for the best soil physical condition. Since the organic matter contents of the cultivated lands in Korea are much lower than optimum level, it would be desiable to use more organic materials to soil for the increase of soil productivity, continuation of stabilized high productivity and soil erosion control.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.533-537
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• 2004

The erodibility of soil is an important factor to scour, especially in fine-grained soils. In this study, the erosion characteristics of kaolinite are quantified through the scour rate tests using the Erosion Function Apparatus called EFA. The basic soil property tests are also performed. The kaolinite samples are prepared by mixing with distilled water and formed to the designed maximum consolidation pressure of 60, 110, 160, 240, 360kPa, respectively. The results of the scour rate tests are presented in a format of a plot showing the relationship between erosion rates and shear stresses. Erosion properties of kaolinite showed a striking contrast according to the maximum consolidation pressure, and a correlation was established between the erosion properties of kaolinite and the soil properties; water content, undrained shear strength, dry density.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.1-10
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• 2003

RUSLE(revised universal soil loss equation) has been widely used for estimating soil loss. It is very difficult to validate the model estimation since the calculated soil loss should be compared with the survey data for quantification. The input variables for RUSLE model were estimated to grid cell for raster analysis in Bosung basin. Both reconnaissance(1:250,000) and detailed(1:25,000) soil maps were used to derive the input variables for soil erodibility factor. Soil loss calculated using RUSLE were compared to the unit sediment deposit surveyed by KICT(Korea Institute of Construction Technology, 1992) in Bosung basin for assessment. Unit sediment deposit from the cell size of 120m and 150m were the closest to the survey data in 1:250,000 and 1:25,000 map scale, respectively.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.188-188
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• 2016

The Mekong which is one of the world's most significant rivers plays an extremely important role to South East Asia. Lying across six riparian countries including China, Myanmar, Thailand, Laos, Cambodia and Vietnam and being a greatly biological and ecological diversity of fishes, the river supports a huge population who living along Mekong Basin River. Therefore, much attention has been focused on the giant Mekong Basin River, particularly, the soil erosion and sedimentation problems which rise critical impacts on irrigation, agriculture, navigation, fisheries and aquatic ecosystem. In fact, there have been many methods to calculate these problems; however, in the case of Mekong, the available data have significant limitations because of large area (about 795 00 km2) and a failure by management agencies to analyze and publish of developing countries in Mekong Basin River. As a result, the Universal Soil Loss Equation (USLE) model in a GIS (Geographic Information System) framework was applied in this study. The USLE factors contain the rainfall erosivity, soil erodibility, slope length, steepness, crop management and conservation practices which are represented by raster layers in GIS environment. In the final step, these factors were multiplied together to estimate the soil erosion rate in the study area by using spatial analyst tool in the ArcGIS 10.2 software. The spatial distribution of soil loss result will be used to support river basin management to find the subtainable management practices by showing the position and amount of soil erosion and sediment load in the dangerous areas during the selected 56- year period from 1952 to 2007.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.4
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• pp.19-27
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• 2012

RUSLE(Revised Universal Soil Loss Equation) has been widely used to estimate the soil loss amount of watersheds from rainfall erosivity, soil erodibility, topographic features and cropping management condition. Rainfall erosivity is the most dominant and sensitive factor among these so that the determination of reliable rainfall erosivity is essential to estimate the soil loss of watershed. Since there has been no criterion to determine the rainfall erosivity in Korea, the empirical values, determined from the relation between the annual average rainfall and erosivity or suggested by TBR(Transport Research Board), have been used for designing the erosion control structure and controlling the soil erosion for watersheds. In this study, the procedure for estimating the rainfall erosivity using frequency analysis is proposed. The most fitted distribution function, with calculated rainfall erosivities with various frequencies and durations, has been also selected. The suggested procedure can be used to estimate the optimal value of rainfall erosivity for RUSLE in order to design soil erosion structures and control the soil erosion in watersheds effectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.1
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• pp.27-37
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• 2001

Soil erosion by outflow of water or rainfall has caused many environmental problems as declining agricultural productivity, damaging pasture and preventing flow of water. As the interest in environment is increasing lately, soil erosion is considered as a serious problem, whereas the systematic regulation and analysis for that have not established yet. This research shows the method of extracting factor entered model which expects soil erosion by GSIS. There are several erosion model such as ANSWER, WEPP, RUSLE. The research used RUSLE erosion model which could expect general soil erosion connected easily with GSIS data. RUSLE's input factors are composed of rainfall runoff factor(R). soil erodibility factor(K), slope length factor(L), slope steepness factor(S), cover management factor(C) and support practice factor(P). The general equation used to extract L, S factor on the RUSLE to be oriented for agricultural area has some limitation to apply whole watershed. So, on this study we used a revised empirical equation applicable to the watershed by grid on the GSIS. Also, we analyzed RUSLE factors by watershed being analyzed with watershed extraction algorithm. Then we could calculate the minimum, maximum. mean and standard deviation of RUSLE factors by watershed.

• Korean Journal of Soil Science and Fertilizer
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• v.21 no.3
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• pp.241-245
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• 1988

The characteristics of some hillside soils in Yeongnam area were investigated to obtain the basic informations for reclamation. Some physico-chemical properties of the soils were discussed with erodibility factor (K) and aggregate stability. The domain clay mineral of soils was identified as Kaoline. Their exchangeable AI, Fe contents were high, and phosphate adsorption coefficients were ranged from 246 to 551 p mg/100g. The improvement of their physico-chemical properties is required in advance to reclaim at those soils.

• Geomechanics and Engineering
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• v.18 no.5
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• pp.493-502
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• 2019

Internal stability is an important safety issue for levees, embankments, and other earthen structures. Since a large part of the world's population lives near oceans, lakes and rivers, floods resulting from breaching of dams can lead to devastating disasters with tremendous loss of life and property, especially in densely populated areas. There are some main factors that affect the internal stability of dams, levees and other earthen structures, such as the erodibility of the soil, the water velocity inside the soil mass and the geometry of the earthen structure, etc. Thus, the mechanism of internal erosion and stability of soils is very complicated and it is vital to investigate the assessment methods of internal stability of soils in embankment dams and their foundations. This paper presents an improved support vector machine (SVM) model to predict the internal stability of soils. The grid search algorithm (GSA) is employed to find the optimal parameters of SVM firstly, and then the cross - validation (CV) method is employed to estimate the classification accuracy of the GSA-SVM model. Two examples of internal stability of soils are presented to validate the predictive capability of the proposed GSA-SVM model. In addition to verify the effectiveness of the proposed GSA-SVM model, the predictions from the proposed GSA-SVM model were compared with those from the traditional back propagation neural network (BPNN) model. The results showed that the proposed GSA-SVM model is a feasible and efficient tool for assessing the internal stability of soils with high accuracy.